1. Technical Field
Embodiments of the present invention relate to techniques of generating image data with an imaging device, such as a digital camera. More specifically embodiments of the invention pertain to techniques of detecting edges in a color filter array image having a mosaic arrangement of fine color filters of R (red), G (green), and B (blue) corresponding to three primary colors of light.
2. Related Art
With the advancement of digital techniques, images are generally processed as digital data (image data). Imaging devices such as digital cameras enable immediate output of captured images in the form of image data. The imaging device is typically equipped with an electronic image sensor consisting of small elements for converting the light intensities into electric signals. The imaging device focuses a captured image of a subject on the image sensor by means of an optical system and detects the light intensities in the individual elements as electric signals to generate image data. The light entering the optical system may be divided into three color components R, G, and B corresponding to three primary colors of light. The respective color lights of the three color components R, G, and B are directed to the image sensor, and the electric signals representing the light intensities of the respective color components acquired by the sensor are output to generate color image data.
The simplest method of acquiring the respective color lights of the three color components R, G, and B, which are obtained as divisions of the light entering the optical system, by the image sensor uses a spectroscopic prism to divide the incident light into the color lights of the three color components R, G, and B and focuses the respective color lights on image sensors to generate image data with regard to the respective color components R, G, and B. This method undesirably requires the three image sensors. One extensively used technique allocates one of the R, G, and B color components to each of the elements constituting the image sensor to attain detection of the respective color components R, G, and B by one image sensor. A typical configuration of this technique provides small color filters allowing transmission of only the R component in front of the elements assigned for detection of the R component, small color filters allowing transmission of only the G component in front of the elements assigned for detection of the G component, and small color filters allowing transmission of only the B component in front of the elements assigned for detection of the B component. This configuration enables simultaneous detection of the image data of the three color components R, G, and B by one image sensor. In the technique of detecting the respective color components R, G, and B by one image sensor, each element assigned for detection of a predetermined color component (for example, the R component) is unable to detect the other color components (for example, the G component and the B component). The resulting image data accordingly has a mosaic arrangement of pixels of the R component, pixels of the G component, and pixels of the B component. Interpolation of missing color components in each pixel with color components of adjacent pixels enables generation of color image data with the settings of all the color components R, G, and B in all the pixels.
An imaging device relying on three image sensors to convert the divisional color lights of the three color components R, G, and B into electric signals and generate image data of the respective color components R, G, and B is occasionally called a ‘three image sensor’ device. An imaging device that uses only one image sensor to generate image data of a mosaic arrangement and compute the missing color components by interpolation is occasionally called a ‘single image sensor’ device. The process of interpolating the missing color components in the image data of the mosaic arrangement to generate color image data with the settings of all the color components R, G, and B is sometimes referred to as a ‘demosaicking process’.
A number of image processing operations such as demosaicking, spatial interpolation, and image denoising and enhancement rely on edge detection in order to direct processing operations along the edges present in the captured image data, thus avoiding processing errors. Edges are important features of digital images since they provide an indication of the shape of the objects in the image.
Typical edge detection processes involve comparing the gradients, square differences, or some other distance or (dis)similarity measures between two or more pixels with a predetermined or adaptive threshold(s). Such comparisons allow distinguishing between true edges and signal discontinuities due to data variations and noise present in the image. However, use of adaptive thresholds in typical edge detection processes can be computationally demanding whereas fixed thresholds may not allow accurate edge detection in images of complex scenarios with varying statistics.